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Added 10 days ago
Lead Software Engineer
RBC
Toronto, ON
Full-time
Experience with advanced GitHub workflows, including Pull Requests, and Actions.
Added 2 days ago
Sr. Integration Architect - Automation
Infotree Global Solutions
Toronto, ON
Contract
Expert-level Senior Integration Developer with Intelligent Automation experience to design, build, and govern mission-critical enterprise automation and integration solutions on Workato and…
Added 3 days ago
Basic Job Template
Banyan Software
Toronto, ON
· Hands-on experience building with automation/orchestration platforms such as n8n (or a comparable platform) and designing and shipping bespoke applications on AWS. Able to evaluate the…
Added 3 days ago
AI Engineer
Yeshnex IT Solutions
Canada
Contract
…databases, query optimization, Alembic migrations Git, CI/CD, GitHub Actions, ArgoCD Docker and docker-compose Google Cloud Platform (Vertex AI, Cloud Run, BigQuery, Cloud Storage, IAM)…
Added 4 days ago
Presales Solutions Architect
Centrilogic
Toronto, ON
Full-time
This is a senior, client-facing generalist role. You sit between Azure infrastructure, Microsoft AI, data platform modernization and the sales team, and you are the technical voice on…
Added 3 days ago
Senior Integration Engineer
Infotree Global Solutions
Toronto, ON
Contract
Expert-level Senior Integration Developer with Intelligent Automation experience to design, build, and govern mission-critical enterprise automation and integration solutions on Workato and…
Added 4 days ago
Solution Engineer with (GitHub Actions) or Platform Engineer with AI
Zodiac Solutions, Inc
Halifax, NS
Full-time
Role: Solution Engineer with (GitHub Actions) or Platform Engineer with AI
Added 4 days ago
Tech Consultant - Senior Full-Stack Engineer
NTT DATA North America
Vancouver, BC
Other
Experience with Jenkins, GitHub Actions, GitLab CI, or Azure DevOps.
Added 1 month ago
Sr. DevSecOps Engineer
Rogers Communications
Brampton, ON · Toronto, ON
Experience with CICD tools like GitHub Actions, ADO or Jenkins
Added 5 days ago
Sr Integration Engineer (Intelligent Automation)
Russell Tobin
Toronto, ON
$90 to $100 CAD / hour
Contract
Expert-level Senior Integration Developer with Intelligent Automation experience to design, build, and govern mission-critical enterprise automation and integration solutions on Workato and…
Added 5 days ago
Sr. Integration Architect - Automation
Infotree Global Solutions
Toronto, ON
Contract
Expert-level Senior Integration Developer with Intelligent Automation experience to design, build, and govern mission-critical enterprise automation and integration solutions on Workato and…
Added 5 days ago
Lead AI Platform Engineer
EQ Bank
Toronto, ON
Full-time
Partner with architecture, security, cloud, infrastructure, delivery, and application teams to translate solution requirements into secure, supportable, and scalable platform…
Added 6 days ago
Lead AI Platform Engineer
EQ Bank | Canada's Challenger Bank
Toronto, ON
Full-time
Partner with architecture, security, cloud, infrastructure, delivery, and application teams to translate solution requirements into secure, supportable, and scalable platform…
Added 6 days ago
Cloud Engineer
Xanadu
Toronto, ON
Full-time
At Xanadu, we primarily work with AWS, Terraform, Docker, Python, and Github Actions. Proficiency in at least a subset of these technologies is essential.
Added 18 days ago
Senior Data Engineer
TekRek
Canada
Full-time
Experience implementing CI/CD for Databricks workloads using tools such as Azure DevOps, GitHub Actions, or GitLab CI, with the communication skills to present technical solutions directly…
Added 19 days ago
Software Engineer II (Full Stack Developer)
TD
Toronto, ON
Full-time
As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.
Added 20 days ago
Senior Analytics Engineer
Lightspeed Commerce, Inc.
Remote, Canada
Full-time · Remote
A modern, well-maintained stack (Dataform, BigQuery, Looker, GitHub Actions, OpenCode) with active investment in developer experience and tooling
Added 19 days ago
2027 Winter - ECCO, Data Scientist Intern (4 Months)
Royal Bank of Canada
Toronto, ON
Full-time
Our mandate is to enable data science and automated solution that help our team to accelerate our processes and reduce completion time in manual work.
Added 26 days ago
2027 Winter - ECCO, Data Scientist Intern (4 Months)
RBC
Toronto, ON
Full-time
Our mandate is to enable data science and automated solution that help our team to accelerate our processes and reduce completion time in manual work.
Added 26 days ago
2027 Winter - ECCO, Data Scientist Intern (4 Months)
RBC
Toronto, ON
Full-time
Our mandate is to enable data science and automated solution that help our team to accelerate our processes and reduce completion time in manual work.
Added 26 days ago
AI Engineer
Sanofi
Toronto, ON
Full-time
…data-first and AI first organization by empowering everyone with good data. Through custom developed AI products built on world class data foundations and platforms, the team builds value…
Added 18 days ago
Software Engineer
SALT XC
Toronto, ON
Hands-on experience with Google Cloud Platform (GCP), CI/CD pipelines (GitHub Actions, Cloud Build), Docker, and cloud infrastructure management.
Added 1 month ago
DevOps Engineer - BTP Site Reliability Engineering team
SAP
Montreal, QC
Full-time
We are looking for an engineer to join an already established SRE team for the SAP Business AI Platform.
Added 1 month ago
Data Engineer
Irth Solutions
Remote, Canada
Full-time · Remote
…infrastructure companies protect their critical network infrastructure. With nearly three decades of industry experience, Irth serves customers across North America and continues to expand…
Added 1 month ago
Senior Architect (Cloud & FinOps Strategy)
CGI
Toronto, ON
Full-time
Collaborate with CGI practice leads, project managers, and engineers to ensure successful end-to-end solution delivery.

EQ Bank

Lead AI Platform Engineer

Toronto, ON, Canada

Job type: Full-time
Apply by: Oct 15, 2026
Experience: 7+ years of experience in platform engineering, site reliability engineering, DevOps, cloud operations, enterprise IT operations, or production platform support.
Posting language: English
Posted: Sep 15, 2026

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Original job description

Purpose Of The Job

The Lead AI Platform Engineer is accountable for technical leadership, engineering excellence, reliability, operability, and the controlled enablement of the organization’s enterprise AI platforms.

This role provides hands-on technical leadership across AI platform design, implementation, automation, observability, and production readiness. The incumbent ensures AI platform services and solutions are secure, resilient, observable, supportable, and compliant with enterprise standards for reliability, security, platform management, monitoring, incident coordination, and governance control enforcement.

The incumbent acts as a senior technical lead for platform engineering activities, guiding implementation decisions, establishing engineering patterns, mentoring team members, and partnering with cross-functional stakeholders to enable the safe and scalable adoption of AI across the enterprise.

Main Activities

AI Platform Engineering Leadership, Reliability and Operations

Lead the engineering, configuration, and operation of enterprise AI platforms to ensure availability, performance, resilience, and scalability across environments, integrations, and supporting infrastructure.
Define and implement platform engineering patterns, standards, reusable components, and operational guardrails that support secure and reliable AI solution delivery.
Provide technical leadership for platform triage, incident resolution, escalation coordination, and post-incident reviews to strengthen service stability and resilience.
Track and report on service reliability indicators, incident trends, engineering risks, and operational performance improvements.

AI Platform Enablement, Solution Readiness, Production Readiness and Technical Delivery

Lead technical enablement of approved AI use cases into non-production and production environments by ensuring environment readiness, dependency validation, release readiness, operational supportability, and service transition planning.
Partner with architecture, security, cloud, infrastructure, delivery, and application teams to translate solution requirements into secure, supportable, and scalable platform implementations.
Guide platform lifecycle management through release coordination, change readiness validation, maintenance planning, capacity planning, and technical risk mitigation.
Ensure AI platform changes meet defined engineering, operational, security, and control readiness criteria prior to release.

Observability, Automation and AI Ops Engineering

Design, implement, and continuously improve observability capabilities, including telemetry, logging, metrics, traces, dashboards, and alerting required for enterprise AI operations.
Lead automation initiatives using approved tools and practices to reduce manual effort, improve reliability, and standardize repeatable operational activities.
Analyze operational data to identify anomalies, recurring issues, root-cause patterns, performance bottlenecks, and opportunities for proactive service improvement.
Implement AI Ops use cases such as alert correlation, anomaly detection, forecasting, root-cause support, knowledge retrieval, and automation of repetitive operational tasks.
Mentor engineers on observability, automation, troubleshooting, and service reliability practices.

Governance, Risk and Control Engineering Execution

Embed governance, security, privacy, auditability, traceability, and human oversight requirements into AI platform engineering and operational practices.
Ensure platform implementations align with enterprise security policies, risk controls, compliance requirements, architecture standards, and operational readiness expectations.
Partner with security, risk, compliance, architecture, and data teams to assess implementation risks, close control gaps, and enable responsible deployment of AI capabilities.
Maintain documentation and evidence required for audit, governance reviews, production readiness checkpoints, and control validation.
Identify technical and control risks, recommend mitigation options, and escalate appropriately to relevant governance and risk stakeholders.

AI Asset Visibility, Platform Integrity, Operational Integrity and Engineering Standards

Maintain engineering and operational visibility of AI platform assets required for monitoring, support, ownership, lifecycle management, and cost alignment.
Validate asset ownership, relationships, configuration integrity, and lifecycle status in collaboration with application, platform, architecture, and infrastructure owners.
Establish and promote engineering standards, reusable patterns, documentation, and technical practices that improve platform supportability and operational integrity.

Knowledge/Skill Requirements

University degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent practical experience.
7+ years of experience in platform engineering, site reliability engineering, DevOps, cloud operations, enterprise IT operations, or production platform support.
Demonstrated experience leading technical delivery, engineering standards, production readiness, incident response, problem management, service restoration, and operational reporting for enterprise platforms.

Technical Expertise

Advanced experience with cloud platforms, observability, automation, configuration management, and integration patterns, including Azure Automation runbooks, Azure AI, Copilot integrations, AKS, virtual networks, App Service, and supporting Azure services.
Strong expertise with observability tools such as Azure Monitor, Application Insights, Log Analytics, Grafana, dashboards, alerting, and operational telemetry design.
Strong experience with CI/CD, automation, and infrastructure-as-code tools such as Azure DevOps, GitHub Actions, Logic Apps, Bicep, Terraform, Azure Policy, Key Vault, and related open-source technologies.
Knowledge of integration and event-driven technologies such as API Management, open-source API tools, Service Bus, Event Grid, and Apache Kafka.
Working knowledge of platform-supporting data and search services such as Elastic, Azure AI Search, Cosmos DB, and related data platform capabilities.
Knowledge of enterprise network, edge security, identity, access management, and related internal platforms such as DNA, Fortinet, and Akamai is an asset.

Additional Capabilities

Strong working knowledge of AI/ML operational concepts, including model lifecycle support, platform telemetry, governance controls, human-in-the-loop practices, responsible AI considerations, and production monitoring.
Strong understanding of ITIL/ITSM processes, including change, release, incident, problem, configuration, service reporting, and operational risk practices.
Proven ability to provide technical leadership, mentor engineers, influence standards, guide implementation decisions, and coordinate complex cross-functional delivery.
Analytical and structured thinker with advanced troubleshooting, root-cause analysis, prioritization, risk assessment, and continuous improvement skills.
Strong service orientation, professional maturity, and the ability to collaborate effectively across operations, engineering, security, risk, data, architecture, and business teams.
Experience creating technical documentation, engineering patterns, operational procedures, support playbooks, dashboards, and user guidance materials.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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More about this job

Responsibilities

Lead the technical design, implementation, and operational reliability of enterprise AI platforms to ensure scalability and security. Drive observability, automation, and governance frameworks to enable the safe adoption of AI use cases across the organization.

Requirements

Requires a university degree in Computer Science or a related field and over 7 years of experience in platform engineering, SRE, or DevOps. Must possess advanced expertise in Azure cloud services, observability tools, and CI/CD pipelines.

Skills

AI Platform Engineering
Site Reliability Engineering
Azure AI
Azure Kubernetes Service (AKS)
Infrastructure as Code
CI/CD
Observability
Azure Monitor
Terraform
Bicep
GitHub Actions
AI Ops
Governance Risk and Compliance
Technical Leadership
Incident Management
Cloud Operations

Visa sponsorship

Not detected in the job text

Keywords

Azure
Copilot
AKS
Azure Monitor
Application Insights
Log Analytics
Grafana
Azure DevOps
GitHub Actions
Logic Apps
Bicep
Terraform
Azure Policy
Key Vault
API Management
Service Bus
Event Grid
Apache Kafka
Elastic
Azure AI Search
Cosmos DB
Fortinet
Akamai
ITIL
ITSM
MLOps
Responsible AI
Financial Services
Platform Engineering
SRE

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